Analysis of traffic flow signals plays an important role in prediction and management. As intrinsic property, the singular point a signal labels new nonsteady status. Therefore, detecting is effective approach to determine moment prediction. In this paper, improved wavelet transform proposed detect points real-time signals. The number detected output via heuristic selection multiple scales. The...

This paper presents a method for freely drawing a graphical password. The new method achieves better security than conventional textual passwords and other graphical password schemes. With this method it is also easier for a user to remember the password. The basic idea of the new method is to use a number of the user's representative sample drawings to predict the user's future drawing predict...

Support vector machine (SVM) is one of the most popular and promising classification algorithms. After a classification rule is constructed via the SVM, it is essential to evaluate its prediction accuracy. In this paper, we develop procedures for obtaining both point and interval estimators for the prediction error. Under mild regularity conditions, we derive the consistency and asymptotic norm...

This paper deals with the effect of small prediction horizon in Neural Generalized Predictive control. A different strategy is proposed to overcome the problem of estimation at each sampling instant. In this method the parameter are estimated at a large sampling interval and control increments are calculated at a smaller sampling interval. Simulation studies are presented to show the merits of ...

The objective of present article is to study the behavior of Bayes prediction length of interval under Two Sample Bayes prediction scenario. A repairable system is considered here with assumption that the repair hazard rate increases monotonically as time parameter increases. Based on right item censoring criterion, the Bayes prediction length of interval and Highest Posterior Density (HPD) int...

This paper introduces two methods for estimating reliable prediction intervals for local linear least-squares regressions, named Bounded Oscillation Prediction Intervals (BOPI). It also proposes a new measure for comparing interval prediction models named Equivalent Gaussian Standard Deviation (EGSD). The experimental results compare BOPI to other methods using coverage probability, Mean Interv...

Prediction interval is awidely used tool in industrial applications to predict the distribution of future observations. The exact minimum coverage probability and the average coverage probability of the conventional prediction interval for a discrete random variable have not been accurately derived in the literature. In this paper, procedures to compute the exact minimumconfidence levels and th...

Because there are new projects on the determination of hyperfine interval in ground state muonium, we revisit different approaches to constructing its theoretical prediction and comparison with experimental data. We discuss a controversy accuracy two recent predictions [Mohr et al., Rev. Mod. Phys. 88, 035009 (2016), Eides, Lett. B 795, 113 (2019)] produce constraint possible systematic errors ...